To meet the performance demands of modern architectures, compilers
incorporate an ever-increasing number of aggressive code
transformations. Since most of these transformations are not
universally beneficial, compilers traditionally control their
application through predictive heuristics, which attempt to
judge an optimization's effect on final code quality a priori.
However, complex target architectures and unpredictable optimization
interactions severely limit the accuracy of these judgments, leading
to performance degradation because of poor optimization decisions.

This performance loss can be avoided through the iterative
compilation approach, which advocates exploring many optimization
options and selecting the best one a posteriori. However,
existing iterative compilation systems suffer from excessive compile
times and narrow application domains. By overcoming these
limitations, Optimization-Space Exploration (OSE) becomes the first
iterative compilation technique suitable for general-purpose
production compilers. OSE narrows down the space of optimization
options explored through limited use of heuristics. A compiler tuning
phase further limits the exploration space. At compile time, OSE
prunes the remaining optimization configurations in the search space
by exploiting feedback from earlier configurations tried. Finally,
rather than measuring actual runtimes, OSE compares optimization
outcomes through static performance estimation, further enhancing
compilation speed. An OSE-enhanced version of Intel's reference
compiler for the Itanium architecture yields a performance improvement
of more than 20% for some SPEC benchmarks.